The possibility that the collapse of the wave function in quantum mechanics is a real and ultimately connected to (classical) gravity has been debated for decades, with main contributions by Diósi and Penrose. In particular, Diósi proposed a noise-based dynamical reduction model, which captures the same orders of magnitude for the collapse time suggested by Penrose based on heuristic arguments. This is known in literature as the DP model (Diósi-Penrose). A peculiarity of the DP model is the prediction of spontaneous heating of matter, which can be tested without the need for massive quantum superpositions. Notably, a very similar effect is predicted by recent theoretical approaches to gravity as a classical-only information channel. Here, we reconsider the current constraints on the DP model from spontaneous heating, by analyzing experimental situations not properly considered before. We argue that the the parameter-free version of the DP model is close to be ruled out by standard heat leak measurements at ultralow temperature, with a conclusive exclusion likely within reach with existing technology. This result would strengthen a recent claim of exclusion inferred by spontaneous x-ray emission experiments, which relies on the somewhat stronger assumption that the DP noise field is white up to x-ray frequencies.
Testing spontaneous collapse through bulk heating experiments: estimate of the background noise
自发波函数崩溃的模型预测一个小的加热速率为散装固体,作为耦合到噪声场,导致崩溃的结果。这个速率足够小,以至于地球表面的环境放射性和宇宙射线通量可以掩盖由于自发坍缩而产生的加热。在本文中,我们估计的背景噪声,由于γ辐射和宇宙线μ子通量,在不同的深度。我们证明,低温地下实验在深度约6.5 km.w.e.将具有足够低的背景,以允许使用目前可用的技术检测对于$10^{-16}$ s $^{-1}$的塌陷速率$λ$的整体加热。
Revisiting Thermal Scalability for Large-Scale Superconducting Quantum Systems
Faculty of Information Science and Electrical Engineering, Kyushu University(九州大学信息科学与电气工程学院);Secure System Platform Research Laboratories, NEC Corporation(NEC公司安全系统平台研究实验室);Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), National Institute of Advanced Industrial Science and Technology (AIST)(国立产业技术综合研究所量子AI技术商业研发中心);Advanced Technology Center, National Astronomical Observatory of Japan (NAOJ)(日本国立天文台先进技术中心);Graduate University for Advanced Studies (SOKENDAI)(综合研究大学院大学)